Evidence map›Paper›PMID 24699682›Full record

ArticlePloS one2014

Treatment default amongst patients with tuberculosis in urban Morocco: predicting and explaining default and post-default sputum smear and drug susceptibility results.

Imad Cherkaoui, Radia Sabouni, Iraqi Ghali, Darya Kizub, Alexander C Billioux, Kenza Bennani, Jamal Eddine Bourkadi, Abderrahmane Benmamoun, Ouafae Lahlou, Rajae El Aouad and 1 more

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
30citing papers in PubMed, 3 pooled it
2.0field-weighted citation impact, top 14% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

30 citing papers in PubMed, 3 syntheses or guidelines pooled it, 63 citations in OpenAlex.

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  15. Observational
  16. Improving Treatment Adherence with Integrated Patient Management for TB Patients in Morocco.International journal of environmental research and public health · 2021
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors at 5 institutions in 2 countries.

Imad CherkaouiDirectorate of Epidemiology and Disease Control, Ministry of Health, Rabat, Morocco.
Radia SabouniNational Institute of Hygiene, Ministry of Health, Rabat, Morocco.
Iraqi GhaliMoulay Youssef University Hospital, CHU Ibn Sina, Rabat, Morocco.
Darya KizubUniversity of Washington School of Medicine, Seattle, Washington, United States of America.
Alexander C BilliouxJohns Hopkins University School of Medicine, Baltimore, Maryland, United States of America.
Kenza BennaniNational TB Control Program, Directorate of Epidemiology and Disease Control, Ministry of Health, Rabat, Morocco.
Jamal Eddine BourkadiMoulay Youssef University Hospital, CHU Ibn Sina, Rabat, Morocco.
Abderrahmane BenmamounNational TB Control Program, Directorate of Epidemiology and Disease Control, Ministry of Health, Rabat, Morocco.
Ouafae LahlouNational Institute of Hygiene, Ministry of Health, Rabat, Morocco.
Rajae El AouadNational Institute of Hygiene, Ministry of Health, Rabat, Morocco.
Kelly E DooleyJohns Hopkins University School of Medicine, Baltimore, Maryland, United States of America.
Institut National d'Hygiène du Maroc · MAMinistère de la Santé · MAHôpital El Ayachi · MAJohns Hopkins Medicine · USUniversity of Washington · US

Funding

PK/PD Issues in the Use of New Therapies for the Treatment of TuberculosisK23AI080842 · NIAID · JOHNS HOPKINS UNIVERSITY · PI DOOLEY, KELLY E. · 2009 to 2013
$670k
NIAID NIH HHS K23 AI080842NIAID NIH HHS K23AI080842
6 · The paper itself

Abstract

settingPublic tuberculosis (TB) clinics in urban Morocco.

objectiveExplore risk factors for TB treatment default and develop a prediction tool. Assess consequences of default, specifically risk for transmission or development of drug resistance.

designCase-control study comparing patients who defaulted from TB treatment and patients who completed it using quantitative methods and open-ended questions. Results were interpreted in light of health professionals' perspectives from a parallel study. A predictive model and simple tool to identify patients at high risk of default were developed. Sputum from cases with pulmonary TB was collected for smear and drug susceptibility testing.

results91 cases and 186 controls enrolled. Independent risk factors for default included current smoking, retreatment, work interference with adherence, daily directly observed therapy, side effects, quick symptom resolution, and not knowing one's treatment duration. Age >50 years, never smoking, and having friends who knew one's diagnosis were protective. A simple scoring tool incorporating these factors was 82.4% sensitive and 87.6% specific for predicting default in this population. Clinicians and patients described additional contributors to default and suggested locally-relevant intervention targets. Among 89 cases with pulmonary TB, 71% had sputum that was smear positive for TB. Drug resistance was rare.

conclusionThe causes of default from TB treatment were explored through synthesis of qualitative and quantitative data from patients and health professionals. A scoring tool with high sensitivity and specificity to predict default was developed. Prospective evaluation of this tool coupled with targeted interventions based on our findings is warranted. Of note, the risk of TB transmission from patients who default treatment to others is likely to be high. The commonly-feared risk of drug resistance, though, may be low; a larger study is required to confirm these findings.

Indexed as

Urban PopulationAntitubercular AgentsCase-Control StudiesHumansMoroccoMycobacterium tuberculosisPatient ComplianceRisk FactorsSputumTuberculosisAntitubercular Agents

Identifiers

PMID24699682
PMCPMC3974736
OpenAlexW2081465316

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.